Index Returns Research Articles

Impact of Macroeconomic Movements on Changes in Stock Returns

In the macroeconomic context, the impact of inflation will be felt by all companies in the industry. This condition will affect the performance of the capital market because many companies cannot operate optimally. As a result, the capital market faces high uncertainty. The problem of timeliness in buying or selling shares often makes investors experience losses in investing. This condition indicates that there is a need for an academic study that is able to predict the factors that influence stock returns. This study aims to examine the effects of inflation, exchange rates, and interest rates on stock returns. This study uses a quantitative approach with a causal paradigm. The population in this study is macroeconomic data and stock returns of the Composite Stock Price Index (JCI) during the 2009–2020 period. Data analysis used regression with the classical assumption tests previously carried out, namely normality, autocorrelation, multicollinearity, heteroscedasticity, and linearity tests. The data test program used is eviews-10. The findings revealed that macroeconomics affect stock returns simultaneously; inflation has a negative effect on stock returns; interest rates and exchange rates have a positive effect on stock returns. The results of this study indicate a conformity with the Arbitration Pricing Theory (APT), which states that asset pricing can be predicted by examining macroeconomic factors.

ANALISIS KINERJA PORTOFOLIO MAGIC FORMULA PADA INDEKS LQ45 DI BURSA EFEK INDONESIA

The rapid growth of active investors in Indonesia stock market raises awareness on the importance of investors’ skill needed in analyzing and choosing profitable stock. One of the method knows to analyze profitable stock in the market is Magic Formula introduce by Joel Grenblatt -part of value investing. Magic Formula is a method on choosing a profitable stock in a simple way based on combination of both High Earnings Yield and High Return on Capital. The period use in this research is from 2016 – 2020. This research use LQ 45 stock listed in Indonesia Stock Exchange. This qualitative research used secondary data which is analyzed using backtesting simulation. The result of this research shows that Magic Formula’s Stock Portfolio build based on data consist of different number of stock: 15, 20, and 25 stock; combination of both high Earnings Yield and High Return on Capital. The Magic Formula’s Portfolio formed based on the LQ 45 stock has higher aritmathic average return compare to LQ 45 return and even the 15-stock-based portfolio beat the Indonesia Composite Index average return. However on the CAGR rate of return, the calculation show that the return of the Magic Formula Portfolio below the return of Indonesia Composite Index

Asymmetric volatility spillover between hospitality sub-sectors during COVID-19: evidence from the USA

PurposeThis article examines dynamic volatility spillovers between stock index returns of four main hospitality sub-sectors in US during the coronavirus disease 2019 (COVID-19) pandemic. These are tourism and travel, hotel and lodging, recreational services and food and beverages. Volatility spillovers are explicitly used as accurate and informative proxies for risk contagion between sectors during turbulent times.Design/methodology/approachThe authors employ dynamic conditional correlation-generalized autoregression heteroskedasticity (DCC-GARCH) and wavelet coherence analysis (WCA) to analyze the phenomenon. The authors’ timeframe is divided into three main sub-periods, namely the pre-pandemic, the first wave and the second wave periods.FindingsThis study’s results reveal immense negative shocks in returns of all four sub-sectors on the Black Monday (8th March 2020). Moreover, high volatility persistence was observed during both waves with an exception of tourism and travel which exhibited lower volatility persistence during the second wave. The authors discovered magnified contagion effects between tourism and travel, hotel and lodgment and recreational services during the first wave of the pandemic with tourism and travel being the main volatility transmitter. Lower magnitudes of spillovers were observed between food and beverages and other sub-sectors with a decoupling effect being evident during the second wave.Research limitations/implicationsThis study’s findings contribute to the contagion theory by providing evidence of disproportional volatility spillover among hospitality sub-sectors despite being exposed to similar turbulent economic conditions.Practical implicationsCrucial implications can be drawn from this study’s findings to assist in risk management, asset valuation and portfolio management. The importance of close monitoring, safety measures, international diversification and adequacy of liquid assets during health crises cannot be stresses enough for hospitality firms. Retail investors, speculators and asset managers can take advantage of this study’s findings to design trading strategies and hedge against risk.Originality/valueA body of knowledge pertaining to effects of crises such as COVID-19 on hospitality stocks has been proliferating. Nonetheless, there is still a relative dearth of empirical literature on volatility spillover between hospitality sub-sectors especially during periods of rising economic uncertainties.

Do Extreme CIT Position Changes Move Prices in Grain Futures Markets?

AbstractMost previous studies reject the basic tenet of the Masters Hypothesis that the influx of financial index investments has pressured agricultural futures prices upwards substantially. However, the impact of index investment activities may be more complicated and nuanced than can be detected by the relatively simple linear Granger causality tests used in many previous studies. Our study applies a new cross-quantilogram (CQ) test to weekly index trader positions and returns in four agricultural futures markets. Overall, we find limited support for a significant relationship between extreme index trader position changes and returns, and even less support that increased index trading activities have pushed commodity prices higher.

Ichimoku Cloud Forecasting Returns in the U.S.

Purpose: We show that the Ichimoku Cloud can forecast stock returns in the U.S., Canada, Germany, and U.K. Design/methodology/approach: We use a regression of next months index return regressed on the Ichimoku Cloud entry signal for price crossing above 9 periods, 26 period, 52 periods and a crossover between 9 and 26 periods. The regression slope coefficient is recorded as the risk premium return. We also record the t-statistic and R2 of the model. We note that T-statistics of 1.65 are statistically significant. R2 is economically significant with a value above .5 percent. Findings: This is showing real-time application how the current Ichimoku Cloud signal can predict tomorrow’s stock return. The strongest results occur for lagged values one period in the U.S. which shows initial justification to using the Ichimoku Cloud. We additionally show the Ichimoku Cloud entry signals are strong in regards to T-statistics and R2 when benchmarked on each of the equity markets in the U.S., Canada, Germany, and U.K. Research limitation/implications: The model only considers technical indicators for forecasting risk premium and could benefit from additional indicators or macro fundamentals. Originality/value: This is the first paper to use Ichimoku Cloud in the risk premium forecast framework.

Improving Returns on Strategy Decisions through Integration of Neural Networks for the Valuation of Asset Pricing: The Case of Taiwanese Stock

Most of the growth forecasts in analysts’ evaluation reports rely on human judgment, which leads to the occurrence of bias. A back-propagation neural network (BPNN) is a financial technique that learns a multi-layer feedforward network. This study aims to integrate BPNN and asset pricing models to avoid artificial forecasting errors. In terms of evaluation, financial statements and investor attention were used in this case study, demonstrating that modern analysts should incorporate the evaluation advantages of big data to provide more reasonable and rational investment reports. We found that assessments of revenue, index returns, and investor attention suggest that stock prices are prone to undervaluation The levels of risk-taking behaviors were used in the classification of robustness analysis. This study showed that when betas range from 1% to 5%, both risk-taking levels of investors can hold buying strategies for the long term. However, for lower risk-taking preferences, only when the change exceeds 10 percent, the stock price is prone to overvaluation, indicating that investors can sell or adopt a more cautious investment strategy.

The Russia-Ukraine Conflict, Crude Oil Price, and Transportation Industry Yield

The Russia-Ukraine Conflict had a serious impact on the economy of Russia and Ukraine and even the world, among which oil, banking, entertainment, and other industries were hit hard. Through the fluctuation of the transportation industry index during the Russia-Ukraine Conflict, this paper concluded that the Russia-Ukraine Conflict had a negative impact on the transportation industry in the short term. But in the longer term, the transport index soon leveled off. This paper finds that the global crude oil price index has a significant impact on the transportation industry only in the short term, and the fluctuation is particularly severe in the early stage of the outbreak of Conflict. This paper uses time-series model, VAR and ARMA-GARCH, to capture the impact of this external shock on the yield and volatility of transportation industry. Based on VAR estimation results, this paper finds that the VAR system we use is stationary processes. Further research finds that, through ARMA-GARCH model estimation, the change of international crude oil price will lead to the fluctuation of production of transportation industry. But this effect is delayed, which also reflects the time lag of financial market transmission. In this paper, we find that global crude oil prices have a significant impact on the inventory returns of the transportation industry in the short run. At the beginning of the conflict, returns were volatile, with the magnitude of the oscillations decreasing over time, and while the returns of the transport index were negatively affected by fluctuations in oil prices in the short term, the conflict had little impact on stock returns in the long term.

Research on the Returns of SSE STAR Market Chip Index Based on the ARMA Model

Since 2021, China’s semiconductor industry and chip industry have been in the hot stage. While the scale of the two industries has continued to expand, there are also problems of bubble economy and excessive competition. In the first half of 2022, the stock market has entered an adjustment cycle. In order to predict the returns trend of the adjustment cycle and help investors make reasonable decisions. This paper uses AIC and BIC criteria to determine the order of the model, test the significance of the model and its parameters, then build the ARMA(2,1) model to predict the closing price of the SSE STAR Market Chip Index from January 2nd, 2020 to February 21st, 2022. According to the results, this paper finds out that both fitting effect and forecasting effect are good. The index will maintain a downward trend in the next 30 periods. Through the above empirical analysis, this paper puts forward two suggestions: firstly, in the face of industry differentiation, people need to invest rationally; secondly, semiconductor companies and chip companies should attach importance to mergers and acquisitions.

Estimating time-varying risk aversion from option prices and realized returns

Risk aversion is estimated from risk-neutral densities and realized index returns

The mirror of history: How to statistically identify stock market bubble bursts

This paper proposes a method for detecting bubble phases and the timing of bursts in global stock markets. The study identifies 27 bubbles in 29 global stock market indices over the last century. Using transformations and change-point detection on index returns, we discover that every major bubble has the same two-phase pattern indeed. Although the mechanisms or causes of each bubble are complex and unique, they all follow the same pattern. Thus, our findings suggest that history has a tendency to repeat itself.

Dynamic relationship between equity, bond, commodity, forex and foreign institutional investments: Evidence from India

The interrelationship between equity, bond, commodity and forex movements can provide investors with abundant trading opportunities regardless of whether one market is trending upward or downward. Hence, to understand the interlinkage between markets, this study examines the long-run and causal linkage between forex, G-sec bonds, oil prices, gold rates, foreign institutional investment (FII) flows, and equity market and sectoral index returns. Daily time-series data from August 2012 to August 2021 were considered for empirical analysis. Johansen’s cointegration test revealed that foreign exchanges like USD, Euro, GBP and Yen, oil and gold rates, G-bond returns and FII flows were significantly cointegrated with the stock market and sectoral indices in the long run. Further, Granger causality found a uni-directional relationship between forex rates (i.e., USD, Euro, Yen) and the market, as well as sectoral indices, except Nifty 50 and Nifty IT indices. Oil price movements were found to effectively predict future price changes of Nifty consumer durables, auto, IT indices. Gold prices are useful to predict Nifty-Auto, Bank, Financial Services, Oil & Gas and PSU. The study also found a bi-directional relationship from FII inflows to the stock market and sectoral indices. The findings suggest that forex rates, oil prices and FII flows significantly affect India’s stock market and sectoral performance. The study contributes to the existing literature by comprehensively examining the interlinkage between commodities such as oil and gold, foreign exchanges like USD, Euro, GBP and Yen, G-bond, FII flows and the stock market, and fourteen sectoral indices in the Indian context.

The Impact of Government Response on the US Stock Market during the COVID-19 Pandemic

Although pandemics have occurred with some degree of frequency over the past century, the degree to which social and economic pandemic-related government responses have been used across the globe during the COVID-19 pandemic period has been unprecedented. Using the S&P 500 stock market index return over the period January 2020-June 2021as our dependent variable in a regression-based model, we measure, via a Government Response Index, the extent to which government response impacted stock market returns. We also include the VIX (“fear gauge”), Market Value, Trading Volume, and Price-to-Earnings Ratios to control for other factors that may have impacted the market during the pandemic. Although we found that the VIX was highly negatively correlated with stock market returns during this period, we found very limited evidence of a significant relationship between stock market returns and government response over this time period. Thus, we believe it would be prudent for governments to be more strategic in their approach regarding initiatives if or when a future pandemic should arise, as not all government-related policy initiatives have the intended effect.

Impact of COVID-19 and government interventions on Bursa Malaysia sectors

Purpose The purpose of this paper is to examine the influence of the daily growth in confirmed COVID-19 cases in Malaysia and government interventions on the daily returns of financial times stock exchange Bursa Malaysia Kuala Lumpur Composite Index (FBMKLCI) and eight selected Bursa Malaysia sectorial indices for the period January 29, 2020 to March 31, 2021. Design/methodology/approach This paper adopts the multivariate generalized autoregressive conditional heteroscedasticity model to determine the effects for the entire study period and four sub-periods, i.e. pre-government intervention, movement control order (MCO), conditional MCO (CMCO) and recovery MCO phases. Findings This paper finds no evidence of the effect of the daily growth in confirmed COVID-19 cases on the returns of FBMKLCI and eight Bursa Malaysia sectorial indices for the full study period. However, the former has exerted different effects over the four sub-periods. Sectors that are positively affected for the MCO period are financial services and real estate investment trust. Yet, these sectors are negatively affected for the CMCO period along with the industrial products and services and technology sectors. Sectors that consistently demonstrate statistically insignificant results are construction, energy, plantation and utilities. Originality/value This study makes an initial attempt to investigate the influence of the COVID-19 pandemic on the returns of Bursa Malaysia sectorial indices over different phases of government interventions in Malaysia.

Out-of-Pocket Spending and Work Loss after Common Surgical Procedures Among Working-Age Adults

INTRODUCTION: Half of surgical patients report financial toxicity, which results from direct out-of-pocket (OOP) cost and indirect loss of income. This study aimed to assess the economic impact of common surgical procedures on patient OOP spending and work loss among working-age adults. METHODS: We used the 2017 to 2019 MarketScan Database to identify adults ages 19 to 64 years who underwent 1 of 20 common surgical procedures. These data were linked to the Health Productivity and Management (HPM) Database, which reports work absence and disability for a subset of employers. Outcomes included spending after index operation, disability, and return to work. Multivariable regression models adjusted for patient demographics and clinical variables. To control for secular trends, we used 4:1 propensity score matching using patient and employment variables. RESULTS: We identified 135,480 patients and 541,920 matched controls. Among this cohort, 25% of patients had a nonelective presentation and 12% had an ICU admission. Spending, missed work, and disability for patients linked to the HPM database are shown in the Table. Nonelective presentation was associated with higher OOP spending and more short-term disability (p < 0.05). Patients requiring ICU stay had higher OOP spending and more missed days of work and disability (p < 0.05). Table. - Six Month Out-of-Pocket Spending and Missed Work after Common Surgical Procedures Variable Surgical patients Matched controls Difference p Value Mean OOP spending (median, IQR) $3,487 ($2,020, $749-3,597) $636 ($12, $0-422) $2,851 <0.001 Any missed work 62.1% 32.5% 29.6% <0.001 Mean total days missed (median, IQR) 23 (15,4-36) 3 (2, 0-4) 20 <0.001 Any short-term disability 36.2% 2.7% 33.5% <0.001 Mean total days of short-term disability (median, SD) 41 (32, 19-56) 35 (15, 0-54) 6 <0.001 Surgical cohorts include common cardiac, vascular, general, and orthopedic procedures. OOP spending represents coinsurance, copays, and deductibles per patient. Missed work and short-term disability outcomes are only for those linked to the HPM database and employed at time of index admission. CONCLUSION: Patients recovering from operation face high OOP payments, miss over a month of work on average, and one in three receive short-term disability benefits. These findings demonstrate the double burden of medical expense and productivity loss and can inform policies for improved financial risk protection after operation.

Impact of Investor Sentiment, Exchange Rates, and Foreign Capital Flow on Jakarta Islamic Index Stock Returns

This study examines the impact of investor sentiment, changes in exchange rates, and foreign capital flow on the Jakarta Islamic Index's return. This study uses daily data between January 2, 2017, and December 30, 2021. After examining the characteristics of autocorrelation and stationarity, we apply the Difference-Generalized Methods of Moment (D-GMM) model. In short, we do not find the effect of investor sentiment on stock returns in both contemporaneous and lag periods. Meanwhile, significant changes in exchange rates have a negative effect on stock returns on contemporaneous and lags, but foreign portfolio flows on contemporaneous and significant lags positively affect stock returns. Thus, our results have implications for trading strategies, asset pricing, and portfolio management carried out by foreign investors on Islamic stocks in Indonesia.

Detecting Regime Changes in Financial Markets using Hidden Markov Models and Directional Changes

The purpose of this study is to construct a multivariate input based Hidden Markov model based on directional changes to detect regime changes in financial markets. For this study, a Hidden Markov Model with multivariate inputs was used. Directional changes were used on historical S&amp;P 500 index returns, additionally, Chicago Board Options Exchange's CBOE Volatility Index along with commonly used index performance indicators were used as inputs to the Hidden Markov Model. The Hidden Markov Model with Directional Change indicators is able to effectively classify regimes on the basis of their statistical properties viz. Mean and standard deviation. The motivation of this study is to model and detect regime changes in US financial markets over the 22-year period from 2000 to 2022. Hidden Markov Models have historically been used by modelling index returns using time series analysis and realised volatility, this paper uses directional changes along with other inputs as observed states to the Hidden Markov Model like the Chicago Board Options Exchange's CBOE Volatility index, 22 and 66 day returns of the S&amp;P 500 index in addition to the 22-day volatility of the S&amp;P 500 index.

The sum of all fears: Forecasting international returns using option-implied risk measures

This paper investigates international index return predictability using daily-updated option-implied information in predictive regressions and out-of-sample forecasts. We document the joint predictive power of a variance risk premium (VRP) proxy (defined as risk-neutral variance minus realized variance), Generalized Riskiness (GR), and higher-order moments for forecast horizons of one day to one year. These four risk metrics, which capture cumulative market “fears,” perform well in the US and in an international sample of countries. The VRP proxy and GR are significant and complementary predictors for several horizons, including under one month (VRP proxy) and longer horizons (GR). Risk-neutral skewness and kurtosis are significant for several countries across multiple horizons. Utility gain calculations confirm the economic significance of these risk-neutral variables across countries.

Regime specific spillover between Dow Jones Islamic Market World Index, Islamic gold-backed crypto currencies and the blockchain halal index

PurposeThe purpose of this paper is to explore the relationship between Dow Jones Islamic Market World Index, Islamic gold-backed cryptocurrencies and halal chain in the presence of state (regime) dynamics.Design/methodology/approachThe authors have used the Markov-switching model to identify bull and bear market regimes. Moreover, the dynamic conditional correlation, the Baba, Engle, Kraft and Kroner- generalized autoregressive conditional heteroskedasticity and the wavelet coherence models are applied to detect the presence of spillover and contagion effects.FindingsThe findings indicate various patterns of spillover between halal chain, Dow Jones Islamic Market World Index and Islamic gold-backed cryptocurrencies in high and low volatility regimes, especially during the COVID-19 pandemic. Indeed, the contagion dynamics depend on the bull or bear periods of markets.Practical implicationsThese present empirical findings are important for current and potential traders in gold-backed cryptocurrencies in that they facilitate a better understanding of this new type of assets. Indeed, halal chain is a safe haven asset that should be combined with Islamic gold-backed cryptocurrencies for better performance in portfolio optimization and hedging, mainly during the COVID-19 period.Originality/valueTo the best of the authors’ knowledge, this paper is the first research on the impact of the halal chain on the Dow Jones Islamic Market World Index return, Islamic gold-backed cryptocurrencies returns in the bear and bull markets around the global crisis caused by the COVID-19 pandemic.

EFFICIENCY INDICES OF INVESTMENT IN IT PROJECTS WITH EQUAL LIVES

Theoretical results not always give an unambiguous answer regarding the preference of using the indices of efficiency of investment in IT projects with equal lives. To complement some of such results, the Net Present Value (NPV), Profitability (PI) and Internal Rate of Return (IRR) indices are researched by computer simulation. In this aim, a model of comparative analysis of projects with equal lives is defined and the SIMINV application is made up. Using SIMINV, the percentage of cases when the solutions, obtained according to indices of each of the pairs {NPV, PI}, {NPV, IRR}, {PI, IRR} or of the triplet {NPV, PI, IRR}, differ for seven groups of alternatives of initial data is determined. Based on done calculations, some properties of indices were identified, including: the quantitative features and the character of dependences on initial data; the average percentage of cases with different solutions, which is of approx. 9 % for the pair of indices PI and IRR, and of 34-35 % for the other two pairs of indices specified above. On average, the solutions of comparing the efficiency of projects with equal lives, obtained using the NPV, PI and IRR indices, does not coincide in more than 1/3 of cases.

AN ASSESSMENT OF COINTEGRATION AND CAUSALITY RELATIONSHIPS BETWEEN BIST 50 AND KATILIM 30 INDICES

Ülkemizin sermaye piyasası platformu Borsa İstanbul'da (BIST) işlem gören KATILIM endeksleri son yıllarda her profilden yatırımcının ilgi odağı olmuştur. Bu çalışmada, BIST 50 geleneksel endeksi ile İslami prensiplere uygun faaliyet gösterdiği belirlenen 30 şirketin hisselerinden oluşan KATILIM 30 endeksi getirileri arasındaki uzun dönemde denge ve kısa dönem ilişkileri araştırılmıştır. Her iki endekse ait veri seti 06.01.2011 tarihinden 30.09.2021 tarihine kadar olan dönemin günlük kapanış değerlerinden oluşmaktadır. Johansen eşbütünleşme analizi sonucunda endeks getirileri arasında uzun dönemde en az 2 eşbütünleşme bulgusu; çift yönlü Granger nedensellik analizi neticesinde ise yalnızca BIST 50 endeksinden KATILIM 30 endeksine doğru tek yönlü istatistiksel olarak anlamlı nedensellik bulgusu saptanmıştır. Buradan hareketle, kısa dönemde geleneksel endekslerin İslami endeks getirileri üzerinde belirleyici bir etkisinin olduğu ve iki farklı metodolojiye dayalı olarak işlem gören bu araçların eşbütünleşik olmaları sebebiyle birbirinden ayrışmadıkları, dolayısıyla Modern Portföy Teorisi çerçevesinde BIST 50 ve KATILIM 30 endeksleriyle yapılacak portföyün yatırımcı açısından faydalı olmayacağı öngörülmüştür.